Abstract

BackgroundAttenuated decreases in lung function can signal the onset of acute respiratory events known as pulmonary exacerbations (PEs) in children and adolescents with cystic fibrosis (CF). Univariate joint modeling facilitates dynamic risk prediction of PE onset and accounts for measurement error of the lung function marker. However, CF is a multi-system disease and the extent to which simultaneously modeling growth and nutrition markers improves PE predictive accuracy is unknown. Furthermore, it is unclear which routinely collected clinical indicators of growth and nutrition in early life predict PE onset in CF.MethodsUsing a longitudinal cohort of 17,100 patients aged 6–20 years (US Cystic Fibrosis Foundation Patient Registry; 2003–2015), we fit a univariate joint model of lung-function decline and PE onset and contrasted its predictive performance with a class of multivariate joint models that included combinations of growth markers as additional submodels. Outcomes were longitudinal lung function (forced expiratory volume in 1 s of % predicted), percentiles of body mass index, weight-for-age and height-for-age and PE onset. Relevant demographic/clinical covariates were included in submodels. We implemented a univariate joint model of lung function and time-to-PE and four multivariate joint models including growth outcomes.ResultsAll five joint models showed that declining lung function corresponded to slightly increased risk of PE onset (hazard ratio from univariate joint model: 0.97, P < 0.0001), and all had reasonable predictive accuracy (cross-validated area under the receiver-operator characteristic curve > 0.70). None of the growth markers alongside lung function as outcomes in multivariate joint modeling appeared to have an association with hazard of PE. Jointly modeling only lung function and PE onset yielded the most accurate (area under the receiver-operator characteristic curve = 0.75) and precise (narrowest interquartile range) predictions. Dynamic predictions were accurate across forecast horizons (0.5, 1 and 2 years) and precision improved with age.ConclusionsIncluding growth markers via multivariate joint models did not yield gains in prediction performance, compared to a univariate joint model with lung function. Individualized dynamic predictions from joint modeling could enhance physician monitoring of CF disease progression by providing PE risk assessment over a patient’s clinical course.

Highlights

  • Attenuated decreases in lung function can signal the onset of acute respiratory events known as pulmonary exacerbations (PEs) in children and adolescents with cystic fibrosis (CF)

  • We focus on multiple longitudinal outcomes and their potential to predict PE onset in children with CF

  • Cohort description The CF cohort for this empirical study consists of patients with longitudinal data recorded from childhood until early adulthood in the US Cystic Fibrosis Foundation Patient Registry (CFFPR) between January 1, 2003, and December 31, 2015

Read more

Summary

Introduction

Attenuated decreases in lung function can signal the onset of acute respiratory events known as pulmonary exacerbations (PEs) in children and adolescents with cystic fibrosis (CF). CF is a multi-system disease and the extent to which simultaneously modeling growth and nutrition markers improves PE predictive accuracy is unknown It is unclear which routinely collected clinical indicators of growth and nutrition in early life predict PE onset in CF. It is of clinical importance to identify an acute respiratory event referred to as a pulmonary exacerbation (PE), which frequently corresponds to sharp decreases in lung function. Patients who experience a PE often fail to recover to their corresponding pre-event (i.e., “baseline”) levels of FEV1 [9] For these reasons, it has been desirable in epidemiologic studies to identify risk factors for having a PE

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call